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European Radiology

, Volume 29, Issue 3, pp 1518–1526 | Cite as

Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules

  • Bao-liang Guo
  • Fu-sheng Ouyang
  • Li-zhu Ouyang
  • Zi-wei Liu
  • Shao-jia Lin
  • Wei Meng
  • Xi-yi Huang
  • Hai-xiong Chen
  • Shao-ming Yang
  • Qiu-gen HuEmail author
Ultrasound
  • 87 Downloads

Abstract

Objectives

The aim of this study was to develop an ultrasound-based nomogram to improve the diagnostic accuracy of the identification of malignant thyroid nodules.

Methods

A total of 1675 histologically proven thyroid nodules (1169 benign, 506 malignant) were included in this study. The nodules were grouped into the training dataset (n = 700), internal validation dataset (n = 479), or external validation dataset (n = 496). The grayscale ultrasound features included the nodule size, shape, aspect ratio, echogenicity, margins, and calcification pattern. We applied least absolute shrinkage and selection operator (lasso) regression to select the strongest features for the nomogram. Nomogram discrimination (area under the receiver operating characteristic curve, AUC) and calibration were assessed. The nomogram was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate a mean AUC and 95% confidence interval (CI).

Results

The nomogram showed good discrimination in the training dataset, with an AUC of 0.936 (95% CI: 0.918–0.953) and good calibration. Application of the nomogram to the internal validation dataset also resulted in good discrimination (AUC: 0.935; 95% CI, 0.915–0.954) and good calibration. The model tested in an external validation dataset demonstrated a lower AUC of 0.782 (95% CI: 0.776–0.789).

Conclusions

This ultrasound-based nomogram can be used to quantify the probability of malignant thyroid nodules.

Key Points

• Ultrasound examination is helpful in the differential diagnosis of malignant and benign thyroid nodules.

• However, ultrasound accuracy relies heavily on examiner experience.

• A less subjective diagnostic model is desired, and the developed nomogram for thyroid nodules showed good discrimination and good calibration.

Keywords

Thyroid nodule Ultrasonography Diagnosis Nomogram Area Under Curve 

Abbreviations

AUC

Area under the curve

CI

Confidence interval

FNA

Fine-needle aspiration

Lasso

Least absolute shrinkage and selection operator

SD

Standard deviation

Notes

Funding

This study has received funding from the science and technology project of Foshan (2017AB003623 and 2017AB003683).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Qiugen Hu

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic study

• performed at two institutions

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of RadiologyShunde Hospital of Southern Medical University (The First People’s Hospital of Shunde)FoshanPeople’s Republic of China
  2. 2.Department of UltrasoundShunde Hospital of Southern Medical University (The First People’s Hospital of Shunde)FoshanPeople’s Republic of China
  3. 3.Department of LaboratoryLecong Hospital of ShundeFoshanPeople’s Republic of China

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